11 citations · 22 across the 17 of their papers we have counts for
5 papers · 1 filter
Wireless Channel Modeling for Machine Learning -- A Critical View on Standardized Channel Models
Benedikt Böck, Amar Kasibovic, Wolfgang Utschick
Standardized (link-level) channel models such as the 3GPP TDL and CDL models are frequently used to evaluate machine learning (ML)-based physical-layer methods. However, in this wo…
Precoder Design in Multi-User FDD Systems with VQ-VAE and GNN
Srikar Allaparapu, Michael Baur, Benedikt Böck +2
Robust precoding is efficiently feasible in frequency division duplex (FDD) systems by incorporating the learnt statistics of the propagation environment through a generative model…
Autoregressive-Gaussian Mixture Models: Efficient Generative Modeling of WSS Signals
Kathrin Klein, Benedikt Böck, Nurettin Turan +1
This work addresses the challenge of making generative models suitable for resource-constrained environments like mobile wireless communication systems. We propose a generative mod…
Sparse Bayesian Generative Modeling for Joint Parameter and Channel Estimation
Benedikt Böck, Franz Weißer, Michael Baur +1
Leveraging the inherent connection between sensing systems and wireless communications can improve their overall performance and is the core objective of joint communications and s…
Physics-Informed Generative Modeling of Wireless Channels
Benedikt Böck, Andreas Oeldemann, Timo Mayer +2
Learning the site-specific distribution of the wireless channel within a particular environment of interest is essential to exploit the full potential of machine learning (ML) for…